ah yes, a nice discussion of the central bank toolkit when policy rates are at their effective lower bound
wait, what's this? Bitcoin and ethereum tickers at the top of the page? A section titled 'Helicopter Money on Blockchain'? hold on a minute...
In fairness, the article did avoid a few of the 'not even wrong' pitfalls you might expect to see written about QE and other sovereign currency monetary operations
Quant is a pretty broad term. Some would say it’s often working on nonlinear desks to implement/calibrate volatility surfaces and things like that or working more on the risk management side. There’s also the whole HFT world (Jane St, Virtu, Jump etc) many would call ’quant’ but really is a different game than the HF space.
On the machine learning side, in my experience it’s often simple, linear models that work best in the messy world of financial data. I’m sure there are shops out there breaking out the GPU clusters and training NNs with 6 trillion parameters but in no way will your super deep NN guarantee alpha whatsoever.
Is an HFT arms race necessarily a bad thing? Doesn’t the market in general benefit from these firms viciously competing to grind out spreads+inefficiencies?
I know very little about HFT, but it seems like we’ve gone past “peak HFT margins”. With the Virtu+KCG merger, firms like Jump doing microwave stuff, it seems like return on assets for these firms could have already peaked.
The authors address this in a few places. The gist is that arbitrage became much faster but not more efficient. Here’s a summary from page 6:
> The usual economic intuition about obvious arbitrage opportunities is that once discovered, competitive forces eliminate the inefficiency. But that is not what we find here. Over the time period of our data, 2005–2011, we find that the duration of ES-SPY arbitrage opportunities declines dramatically, from a median of 97 milliseconds in 2005 to a median of 7 milliseconds in 2011. This reflects the substantial investments by HFT firms in speed during this time period. But we also find that the profitability of ES-SPY arbitrage opportunities is remarkably constant throughout this period, at a median of about 0.08 index points per unit traded. The frequency of arbitrage opportunities varies considerably over time, but its variation is driven almost entirely by variation in market volatility. These findings suggest that while there is an arms race in speed, the arms race does not actually affect the size of the arbitrage prize; rather, it just continually raises the bar for how fast one has to be to capture a piece of the prize.
A famous anecdote along these lines are the whatsapp founders.
I haven’t done so personally yet but it’s starting to look like I might consider this route.
Several years ago, I would have leaned toward a SaaS business targeting some super niche vertical, not to make 1000x VC style rocket-ship returns of course, but as a way to bootstrap into a nice business. I get the sense most verticals with a TAM worth going after are now very competitive.
Interested to see if people see opportunities in non-tech routes.
Another famous anecdote would be Elon Musk, who tried to get a job at Netscape in the '90s and failed [1], and claims that he created his first company because he couldn't get a job at any existing internet companies.
On one hand there are hyper-bulls who claim Tesla is a $4000 stock and the future of transportation. On the other, hyper-bears claim the equity should trade around $0-$10. There seems to be no middle ground.
It seems like they are almost betting the company on FSD. I don’t think FSD is really even close to a possibility over the next 5-10yrs. I hope I’m wrong, but if I’m right, I don’t see how Tesla keeps going on like this.
> On one hand there are hyper-bulls who claim Tesla is a $4000 stock and the future of transportation. On the other, hyper-bears claim the equity should trade around $0-$10. There seems to be no middle ground.
>On one hand there are hyper-bulls who claim Tesla is a $4000 stock and the future of transportation. On the other, hyper-bears claim the equity should trade around $0-$10. There seems to be no middle ground.
Well the middle ground is the actual stock market where Tesla is trading around $265.
> It seems like they are almost betting the company on FSD.
IMO they don't have any choice. The more and longer they operate like a car company shipping bigger and bigger volumes, the more their financials will be undeniably trend towards those of the existing car companies and the more their existing market valuation will be hard to justify.
They need something like this to not get traded at traditional car industry multiples.
If you just measure based on Tesla's last two quarters, their P/E is just 28. That's high for a car company but pretty low for tech. Self-driving is not necessary to maintain that valuation, only continued growth of the electric car market in general.
> That's high for a car company but pretty low for tech.
Yes! Totally agree.
> Self-driving is not necessary to maintain that valuation, only continued growth of the electric car market in general.
Disagree. The key properties of the car business are high capital costs and high variable costs and not huge margins. The key property of the tech business is low variable cost and often low capital costs (but not always) and high margins.
There's nothing "tech" about building electric cars vs. normal cars and 10 years from now the margins and capital expenses of electric car business will be like the existing ICE car business.
So this is Tesla saying: "Yeah, our financials are starting to look like a normal car company, but we've got this thing that you should keep value us even more like a tech company than you do today."
The market values Tesla like a car business that is growing ~50% per annum.
> 10 years from now the margins and capital expenses of electric car business will be like the existing ICE car business.
Tesla already has margins similar to existing car companies.
> So this is Tesla saying: "Yeah, our financials are starting to look like a normal car company, but we've got this thing that you should keep value us even more like a tech company than you do today."
Yes, they're saying that, but the market is obviously not buying it.
I think FSD would be cherry on the top. If they can continue slashing down the prices and improve battery life it would be revolution in itself. Even just continuing with current pace if they can produce $18K electric car with 600 miles range in next 3-5 years, you could be golden as shareholder. Their advantage, like Apple, is attention to details and awesome design that other car manufacturers have failed to replicate.
Isn’t it just one big misunderstanding between them?
Taleb thinks 538’s probabilities represent a binary option price on the event, in which case, yes, the probabilities should stay very close to 50% because the vol is so high. Whereas Silver’s models are actually saying “Based on current polls, if the election were held tomorrow, then the probability candidate X wins is Y%” and are thus allowed to swing more wildly. Aren’t both just fundamentally different things or am I missing something in Taleb’s argument?
This makes perfect sense to me. But it shouldn't be 50%, it should be "regression to the mean" where the mean is a "naive" forecast based on history, the economy, demographics, etc, etc, etc.
Silver is making a prediction based on the best model that he has.
It isn't quite arbitrage, but if you did binary option pricing then you could indeed fairly safely make money off of Silver by taking known events that you know swing polls, like conventions, and betting on the likely pricing changes.
That said, the data set that Silver is developing using his model is going to be one of the key inputs into a more sophisticated pricing model. And how to factor in those other external factors is going to require a lot of calibration between Silver's predictions and a known database of such external factors. Which means that Silver's approach is the right starting place to get there, no matter how much Taleb might wish it otherwise.
A forecast that really did try to be an option pricing model like that would be interesting to see. It would have the advantage over a “now cast” that you could actually run the numbers and see how accurate it is. Whereas nobody can ever know what would actually happen if there were an election now rather than a year from now.
> A forecast that really did try to be an option pricing model like that would be interesting to see.
Silver’s election forecast models are exactly that. The nowcast expressly is not, but it's also not the headline model.
> It would have the advantage over a “now cast” that you could actually run the numbers and see how accurate it is.
That's true, and not just in theory: Silver has recently run the numbers for all of 538s forecasts (together and separated by sports vs. elections) and they are relatively accurate but not perfect; the supporting data is available for download, too.
Aha, thanks for clarifying that. I actually read that article, but the earlier comment got me confused over whether it was merely validating the final forecasts, or all forecasts over time.
Makes sense that it was written as an explicit rebuttal to Taleb -- but without mentioning him directly. :)
I don't think your assessment of 538's models is correct. They used to have something called the "nowcast" which is what your referring to, but they got rid of that.
As was mentioned elsewhere in this thread (and I am aware of from reading 538) during the campaign, Silver updates separately both a probability based on the scenario of "if the election were held tomorrow" and the best prediction of the election on its actual date.
In the 2016 election season, Silver used three models, two forecast models predicting what the election would do (a “polls-only” and a “polls-plus” model incorporating non-poll data), and the “nowcast” of what would happen if the election were held at the moment of the analysis. The polls-only forecast was (at least at the end of the cycle) the headline result.
Taleb calling someone else an entertainer is a bit rich, sort of like a clown telling someone to have dignity. I have no opinion on Silver whatsoever, but Taleb is a bloviating ass who has gone from popular milquetoast observations, to climbing fully up his own backpassage. That this all began with the likes of Dinesh D’Souza doesn’t help.
I realize that Black Swan is popular here, but it was horrendous. A single essential premise which, instead of support, rested for chapter after chapter on assertions. That’s not evidence, it wasn’t an argument, it was the sound of someone having one good idea and then realizing they lacked the capacity to support it.
Quantifying the current voter sentiment makes you a entertainer? If anyone should be accused of "entertainment", I'd imagine it's the guy known for writing mass-market books.
GP doesn't even have Silver’s model right (he describes the “nowcast”, which was never the headline forecast model), so if he is right that that is what Taleb is referring to, that would be a pretty damning indictment of Taleb’s critique.
I don’t work at FAANG, but the general sense I get is that while there is no doubt top DL talent that should command mid six to seven figure salaries, it seems that with AI programs stuffed at both the undergrad and grad levels that things should cool off eventually.
More broadly, does success in academia usually translate to delivering business value? Are these companies betting on these researchers to come up with the next great DL architecture?
I'm not in academia or at a FAANG, but I think that talented professors should always have applicable skills. A professor successfully running a research lab is basically running a small company. They need to raise grant money, and then deliver results, all while needing to mentor their employees. Because most of their workers will be students and leave after graduation.
So if you define top talent to be research lab or publication success I think that top talent will always be attractive corporate RD, assuming there's a match in the research area. I don't really know how these companies are evaluating their RD, so delivering business value is another question.
Ian Goodfellow already has come up with the next great DL architecture. So its possible he will do so again.
edit: thinking about your question more-as an AI person I think the business logic behind hiring AI research talent if you are FAANG is not that they are going to deliver much business value in the next five years but they may deliver astronomical returns in the next 25 years. when you have the financial strength of google hiring these people is not a very large risk.
Looking at that odds chart got me in a betting mood. I think those Yang odds in the article could be steep given the exuberance of some in his online following, however there could be interesting arb plays with an outsider like Yang like going long presidency+short nomination paired with going short presidency+long nomination with someone more establishment like Biden.
If prediction markets had more depth, I’m sure we would see politics hedge funds emerge.
You’re right. Like a lot of other engineers, I once thought “ML+High level team info=$$$$” but quickly learned that you really can’t get an edge unless you’re digging into that more granular data and even then it’s really tough. It can be very hard to improve on simple linear models.
The odds coming out of Vegas are usually priced correctly. Sports markets are very efficient—although perhaps not as ruthlessy efficient as public equity markets. I would imagine there are still syndicates out there that are the “RenTec of sports betting” and just printing alpha.
I just heard about this on Patrick O’Shaughnessy podcast. As a coffee-fiend, I really should look into becoming a customer, and am also interested to see what offerings come next.
Reminds me of a Whitehead quote that I like that can also serve as a heuristic to evaluate business ideas:
“Civilization advances by extending the number of important operations which we can perform without thinking about them”
I love that literally everything is abstracted away from the customer. Stuff just appears like magic.
wait, what's this? Bitcoin and ethereum tickers at the top of the page? A section titled 'Helicopter Money on Blockchain'? hold on a minute...
In fairness, the article did avoid a few of the 'not even wrong' pitfalls you might expect to see written about QE and other sovereign currency monetary operations